Pharmacy · Fill Rate · SAP · CFO

Fill Rate Monitoring: Pharmacy retail, SAP data, Finance decisions

A pharmacy CFO on SAP should not be hunting for fill rate problems. Ward surfaces them on a daily cycle.

The full picture: pharmacy fill rate, SAP data, Finance decisions

What fill rate monitoring does: Ward monitors on-shelf availability across your entire estate and flags stores or categories dropping below threshold.

In a Pharmacy & Health fleet the job is 20,000+ SKUs across pharmacies. Regulated inventory, seasonal demand spikes, and front-of-store optimization. Ward handles the complexity so your pharmacists focus on patients.

Your P&L surprises are born on the store floor. Ward filters to what a CFO can act on and drops the rest.

How it runs. Ward tracks expected vs actual on-shelf availability at the store-category level and escalates when fill rate drops below configurable thresholds.

How the connection works. Ward reads from SAP via RFC/BAPI or OData APIs. No changes to your SAP configuration. Read-only access. Data syncs on your schedule.

Capabilities

  • Store-vs-estate benchmarking
  • Category-level drill-down
  • Estate-wide fill rate dashboard
  • Threshold-based alerting
app.getward.ai Live demo
Acme Pharmacy @Merchandising: Front-Store Analyst claude-sonnet default
A

Chat

Ask anything. Ward routes to the right agent and returns cited answers.

Why are we behind on cough and cold in the Northeast?
You · 9:42 AM
Schema Scout · routed to Merchandising Agent

I pulled cough and cold against the illness curve for the 38 Northeast pharmacies. Front of store is running two weeks behind the demand signal.

SignalFinding
otc_sales_dailyCough/cold units +31% WoW, on-shelf availability down to 88%
replenishmentVendor lead time 6 days, reorder points still on the summer baseline
front_store.attachWellness attach on flu-season fills 19% vs. 34% chain best

Recommend: raise cough/cold reorder points at all 38 stores now, pull the wellness endcap forward two weeks, and add the attach prompt at the counter.

8 parallel queries 3 sources cited confidence 0.90
Which stores need the reorder point change first?
You · 9:43 AM
Replenishment Agent · ranking stores
Querying otc_sales_daily
Ask anything, Ward routes to the right agent. Cmd+K

Reporting

Pinned views built from saved data-lake queries. Every number re-derivable from its SQL.

7d13w52w
Front-store revenue
$22.4M
+3.6% WoW
Front-store margin
28.7%
−1.8pp
OTC on-shelf availability
88.1%
−2.9pp
Expiry waste, 60-day risk
1.72%
+0.9pp
Front-store revenue 13 weeks actual, 6 weeks forecast, 80% interval
Actual Forecast 80% interval
% of plan 106 94 100 forecast → W−13 W−5 today +6wk
Holt-Winters + weather regressor MAPE 4.1% at 4wk Backtested 24 months Crosses plan in 3 weeks
Forecast error by horizon MAPE, 24-month backtest
1wk 2.1%
2wk 3.0%
4wk 4.1%
8wk 6.3%
13wk 8.9%
Accuracy bar for promo decisions: ≤5% at 4wk
Models in production Every forecast ships a model card
ModelHorizonMAPE
holt_winters4wk4.1%
arima_sarimax13wk8.9%
gbm_demand1wk2.1%
bayes_hiernew store11.4%

Sources

Connect external systems to the data lake.

NameTypeLast sync
mckesson_wholesale_ordersimport2m ago
cardinal_lot_expiryimport2m ago
sap_pos_transactionsimport14m ago
sap_inventory_snapshotimport1h ago
retail_otc_sales_dailyimport1h ago
retail_front_store_marginimport1h ago
retail_planogram_auditimport1h ago

Policies

Browse and manage Cedar access policies for your tenant.

TLS 1.3 AES-256 Read-only SOC 2 II
Policy IDEffectResources
merch-read-front-storepermitModel::"front_store_margin"
ops-read-defaultpermitModel::*
phi-forbid-allforbidModel::"patient_*"
supply-read-expirypermitModel::"lot_expiry"
Fill Rate for Pharmacy on SAP data, live product demo.

Why Fill Rate matters for Pharmacy retail

Illness demand is hyperlocal and fast-moving, one zip code can spike while another 10 miles away sits at baseline. A single week of empty shelves during a surge pushes customers to Amazon or a competitor. Ward monitors front-of-store fill rate with a focus on illness-sensitive categories, flagging stores depleting faster than standard replenishment can cover.

What Ward has eyes on.

Every empty shelf is a lost sale. Ward runs the model continuously rather than on a reporting cycle, which is why a finding lands the morning the pattern starts instead of at the end of the period.

Coverage is store by store, category by category. Ward scans continuously Rx fill rate, OTC attach rate, expiry waste % across 20,000+ SKUs and compares each store against its own baseline, not against the chain. That is the difference between knowing the footprint is fine and knowing which seven pharmacies are not.

Ward reads POS transactions, inventory positions, purchase orders from SAP Retail on a read-only connection. Nothing is written back, and your ERP configuration does not change. SAP stays the system of record.

At the metric level. Ward focuses on illness-sensitive category availability, seasonal product positioning timing, companion availability alongside high-Rx-volume items, and endcap fill rate as a proxy for promotional execution.

Signals · POS at SKU-store-day, current OTC inventory, Rx fill volume, public health and seasonal surveillance, planogram and endcap compliance reports.

Why this combination
is its own problem.

A generic fill rate model applied to a pharmacy estate produces alerts nobody trusts. The thresholds are wrong, because pharmacy baselines are wrong for it. Ward learns the baseline from your own pharmacies instead of importing one.

  • 01 Estate-wide OTC fill rate looks healthy while specific zip codes hit zero on illness-surge SKUs; the regional signal is buried in the chain average.
  • 02 Companion OTC availability tied to high-Rx-volume conditions (statins → fish oil, metformin → glucose strips) isn't monitored in fill rate dashboards.

Benchmarks. Pharmacy front-of-store fill rate: 95-98% chain average, dropping to 75-85% during illness surges without active region monitoring. Each fill-rate point lost on top-100 OTC SKUs ties to roughly 0.4-0.7% category revenue erosion; on illness-surge categories the multiplier is 2-3x.

What the first 90 days
actually look like.

  1. 01

    Week 1: connect

    Read-only credentials to SAP Retail. Ward ingests POS transactions, inventory positions, purchase orders and starts building baselines. First insight cards land inside 48 hours, before baselines are stable, so you can see the shape of the output early.

  2. 02

    Weeks 2 to 3: baselines

    Ward needs roughly two weeks of history per store to separate a real deviation from normal variance. During this window the daily cards are directionally right and the thresholds are still moving.

  3. 03

    Weeks 4 to 12: steady state

    Ward returns insight cards every morning, each with the driver and a recommended action. Volume settles at a level a single person can read over coffee. The measure of success is not how many findings arrive, it is how many get acted on.

How Ward connects to SAP Retail

Ward connects to SAP Retail (S/4HANA, ECC, CAR) via standard BAPIs and IDocs. Transaction data, inventory positions, and master data flow into Ward without custom development.

Setup: Ward reads from SAP via RFC/BAPI or OData APIs. No changes to your SAP configuration. Read-only access. Data syncs on your schedule.

Data Ward reads from SAP

POS transactions
Inventory positions
Purchase orders
Material master
Vendor master
Promotion calendar

Impact metrics with SAP

Replenishment Accuracy
Gaps flagged early
Inventory positions matched to POS velocity before shelf impact.
Shrinkage
Anomalies surfaced continuously
Transaction-level detection catches what periodic audits miss.
Forecast Accuracy
External signals layered
Weather, events, and competitor data sharpen SAP demand signals.
Promo ROI
True lift isolated
Sell-through data exposes cannibalization and halo effects.

Data lake enrichment

Ward enriches SAP data with: POS transactions, Weather & events, Competitor pricing, Loyalty & CRM, Supplier fill rates

Your P&L surprises are born on the store floor.

Pain points
  • ×Margin erosion only surfaces at month-end close
  • ×Inventory carrying costs are a black box
  • ×Working capital tied up in slow-moving stock nobody is watching
  • ×Same-store sales comps lack decomposition into actionable drivers
  • ×Capex decisions for store remodels lack unit-economics evidence
How Ward helps
  • GMROI tracking by category with weekly insight cards
  • Inventory carrying cost alerts when capital efficiency drops
  • Working capital optimization recommendations based on turnover trends
  • SSS decomposition into traffic, conversion, and basket components
  • Store-level unit economics cards for capex prioritization

Inventory distortion, overstock and out-of-stock combined, costs retailers $1.77 trillion globally. Source: IHL Group

Pharmacy KPI impact

Expiry Waste
Flagged before close
Shelf-life velocity tracked per store.
Front-of-Store Margin
Highest-margin area
OTC adjacency and illness prep cards for the front end.
OTC Attach Rate
Rx-to-OTC conversion
Seasonal wellness bundling patterns identified.
Fill Rate
48–72hr lead time
Illness demand modeled before seasonal spikes hit.

Frequently asked questions

Ward monitors on-shelf availability across your entire estate and flags stores or categories dropping below threshold. For Pharmacy retail specifically, Ward monitors 20,000+ SKUs across your pharmacies and delivers automated insight cards with root cause analysis and recommended actions.

Ward tracks Rx fill rate, OTC attach rate, Expiry waste %, Script count, Front-store margin at the store-category level. Ward tracks expected vs actual on-shelf availability at the store-category level and escalates when fill rate drops below configurable thresholds.

Ward reads from SAP via RFC/BAPI or OData APIs. No changes to your SAP configuration. Read-only access. Data syncs on your schedule. Data points include: POS transactions, Inventory positions, Purchase orders, Material master, Vendor master, Promotion calendar.

Yes. Ward reads SAP data and combines it with contextual signals (weather, events, demographics) to generate Pharmacy-specific insight cards. No custom development required.

Your P&L surprises are born on the store floor. Ward solves this with automated insight cards: GMROI tracking by category with weekly insight cards. Inventory carrying cost alerts when capital efficiency drops. Working capital optimization recommendations based on turnover trends.

Ward delivers daily insight cards covering Rx fill rate, OTC attach rate, Expiry waste %, tailored for Finance decision-making. Each card includes what changed, why it matters, and what to do next.

Ward focuses on illness-sensitive category availability, seasonal product positioning timing, companion availability alongside high-Rx-volume items, and endcap fill rate as a proxy for promotional execution.

Ward detects fill rates on infant fever reducers and pediatric electrolytes dropping below threshold at stores in a suburban corridor, correlating with a local RSV spike. Standard replenishment is days away. Ward issues an emergency alert recommending immediate transfers from nearby stores with excess inventory and a forward-buy trigger for the coming weeks of elevated demand.

First insight cards arrive within 48 hours of data connection. Ward needs approximately 2 weeks to establish stable baselines for your specific operation.

No. Ward sits on top of your existing stack. It is the proactive intelligence layer that watches your data continuously and delivers insight cards, so your team acts on findings instead of hunting for them.

See what Pharmacy fill rate problems Ward catches.

Root causes, not just alerts. See it on your data.

Read-only to start · your LLM keys · SOC 2 Type II underway · or book a call directly

Find out what your data has been hiding.

Tell us about your operation. We’ll show you the problems Ward catches, and the ones your current tools miss.

Step 1 of 3
What are your goals?
Step 2 of 3
About your operation
Step 3 of 3
Your contact info